Frank MuellerNorth Carolina State University

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PIs & Funding

NSF funding level: $550k

NCSU: $60k (ETF) + $20+k (CSC)

NVIDIA: donations ~$30k

PIs/co-PIs:

— Frank Mueller

— Vincent Freeh

— Helen Gu

— Xuxian Jiang

— Xiaosong Ma

Contributors:

— Nagiza Samatova

— George Rouskas

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ARC Cluster: In the News

“NC State is Home to the Most Powerful Academic HPC in North Carolina” (CSC News, Feb 2011)

“Crash-Test Dummy For High-Performance Computing” (NCSU, The Abstract, Apr 2011)

“Supercomputer Stunt Double” (insideHPC, Apr 2011)

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Purpose

Create a mid-size computational infrastructure to support research in areas such as:

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Researchers Already Active

In the first week of public access:

From groups from within NCSU:— CSC, ECE, Chem/Bio Engineering, Materials,

Operations Research ORNL Tsinghua University, Beijing, China

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System Overview

Mid TierFront Tier Back Tier

Head/Login Nodes

IB Switch Stack

GEther Switch Stack I/O Nodes Storage ArrayCompute/Spare Nodes

PFS Switch Stack

Interconnect

SSD+SATA

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Hardware

108 Compute Nodes— 2-way SMPs with AMD Opteron

6128 processors with 8 cores per socket

— 16 cores per node!— 32 GB DRAM per node

1728 compute cores available

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Interconnects

Gigabit Ethernet

— interactive jobs, ssh, service

— Home directories

40Gbit/s Infiniband (OFEDstack)

— MPI Communication

— Open MPI, MVAPICH

— IP over IB

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GPUs

NVIDIA Tesla C2050 (1 login + 36 nodes)— 448 Compute cores per GPU

— Peak GigaFLOPS 515 SP/1030 DP

— Memory Amount 3GB

— Memory Interface 384-bit

— Memory Bandwidth (GB/sec) 144

NVIDIA GTX480 (10 nodes)— 480 Compute cores per GPU

— Peak GigaFLOPS 1344.96 SP/ 168DP

— Memory Amount 3GB

— Memory Interface 384-bit

— Memory Bandwidth (GB/sec) 177.4

NVIDIA Tesla C2070 (2 nodes)— 448 Compute cores per GPU

— Peak GigaFLOPS 515 SP/1030 DP

— Memory Amount 6GB

— Memory Interface 384-bit

— Memory Bandwidth (GB/sec) 144

NVIDIA 1060 GTX (1 node)

NVIDIA 8800 GTX (1 node)

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Solid State Drives

All 108 compute nodes equipped with

OCZ RevoDrive 120GB SSD

— Read: Up to 540 MB/s— Write: Up to 480 MB/s— Sustained Write: Up to 400 MB/s— Random Write 4KB (Aligned): 75,000 IOPS

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File Systems

Available Today:— NFS home directories over Gigabit Ethernet— Local per-node scratch on spinning disks (ext3)— Local per-node 120GB SSD (ext2)

In the future:— Parallel File Systems

–Lustre–Separate dedicated nodes are available for parallel filesystems–1 MDS + 4 clients

Are you interested in helping us set this up for your research projects??

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Power Monitoring

Watts Up Pro— Serial and USB available.

Connected in groups of:— Mostly 4 nodes (sometimes just 3)— 2x 1 node

– 1 w/ GPU– 1 w/o GPU

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Software Stack

Additional packages and libraries— upon request but…— Not free? you need to pay— License required? you need to sign it— Installation required? you need to

–Test it–Provide install script

check ARC website constantly changing

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Base System

64bit Rocks 5.3 (based off of CentOS)

Batch system:— Torque/Maui (PBS)

All compilers and tools are available on the login nodes.

— Gcc, gfortran, …— Compute nodes share the same base OS and

libraries as the login nodes.

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MPI

Open MPI— Operates over Infiniband— Integrated with BLCR— Already in your default PATH

–mpicc

MVAPICH— Infiniband support— Requires changes to your path. See ARC site.

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OpenMP

The "#pragma omp" directive in C programs works.

gcc -fopenmp -o fn fn.c

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CUDA SDK

Ensure you are using a node with a GPU— Several types available to fine tune for your applications

needs:–Well-performing single or double precision devices.

Requires environment changes:export PATH=".:~/bin:/usr/local/bin:/usr/bin:$PATH“

export PATH="/usr/local/cuda/bin:$PATH“

export LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/lib:$LD_LIBRARY_PATH“

export MANPATH="/usr/share/man:$MANPATH“

Or see site to make sure you have the latest paths…

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PGI Compiler (Experimental)

Awaiting site license update.

export PATH=".:~/bin:/usr/local/bin:/usr/bin:$PATH“

export PATH="/usr/local/cuda/bin:$PATH“

export LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/lib“

export MANPATH="/usr/share/man“

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Virtualization

Goal: To allow a user to request VMs from the batch system just like they would any other resource

— User gets full root access to each VM requested with complete control over that VM.

— VMs will share the same network or may be grouped together into private networks across single or multiple nodes.

Elegant VM creation scripts in place allow entire machine creation in a single line.

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Job Submission

cannot SSH to a compute node

must use PBS to submit jobs— Either as batch — or interactively

Presently there are “hard” limits for job times and sizes. In general, please be considerate of other users and do not abuse the system.

There are special queues for nodes with a GPU— As we add additional specialized resources even more

queues will become available.

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PBS Basics

On the login node:— to submit a job: qsub …— to list your jobs: qstat— to list everyone’s jobs: qstat –a— to delete/cancel/stop your job: qdel …— to check node status: pbsnodes

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qsub Basics

qsub -q cuda ... # job submitted to GPU/CUDA queue

qsub -l ncpus=4 ... # ask for four tasks (processors) -- packed as up to 16 tasks per node

qsub -l nodes=4:ppn=16 ... # job for four nodes with 16 processors on each node (64 tasks)

qsub -l nodes=2:ppn=1 -q cuda ... # job for two tasks on two nodes with GPU/CUDA support

qsub -l nodes=2,cput=00:5:00 ... # job for two tasks + 5 minutes CPU time

to submit interactive: qsub -I # one node, shell will open up

to submit interactive: qsub -I -nodes=20 #two nodes w/ 20 tasks

to submit interactive: qsub -I -l host=compute-0-54.local #specifically on node 54

to submit interactive: qsub -I -l host=compute-0-54.local+compute-0-55.local #on 54+55

to submit interactive with X11: qsub -I -X ...

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Listing your nodes

Once your job begins, $PBS_NODEFILE points to a file that contains a list of your requested nodes.

Open MPI is already integrated with PBS. Simply using mpirun … will automatically use all requested processes directly from PBS.

For example, a CUDA programmer that wants to use 4 GPU nodes:

[dfiala@login-0-0 ~]$ qsub -I -lnodes=4:ppn=1 -qcuda

qsub: waiting for job 1774.arcs.csc.ncsu.edu to start

qsub: job 1774.arcs.csc.ncsu.edu ready

[dfiala@compute-0-2 ~]$ cat $PBS_NODEFILE

compute-0-2.local

compute-0-32.local

compute-0-35.local

compute-0-38.local

---SSHing between these nodes FROM the PBS session is allowed---

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Handling problems

If you find a node that is giving you trouble please report it to the mailing list.

As a workaround, you can keep that node busy by queuing an empty job:

echo sleep 600 | qsub -l host=compute-0-100,walltime=1000

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Hardware in Action

4 racks in server room

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Running Large Jobs (and keeping cool)

While our new cluster is surely state of the art…

The cooling system isn’t.

Our “dual action” cooling solutionfor the state of the art cluster

State of the art cluster

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Temperature Monitoring

It is the user’s responsibility to maintain room temperatures below 80 degrees while utilizing the cluster.

— ARC website has links to online browser-based temperature monitors.

— And the building staff have pagers that will alarm 24/7 when temperatures exceed the limit.

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Connecting to ARC

ARC access is restricted to on-campus IPs only.— If you ever are unable to log in (connection gets dropped

immediately before authentication) then this is likely the cause.

Non-NCSU users may request remote access by providing a remote machine that their connections must originate from.

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Summary

Your ARC Cluster@Home: What can I do with it? Primary purpose: Advance Computer Science Research (HPC and

beyond)— Want to run a job over the entire machine?— Want to replace parts of the software stack?

Secondary purpose: Service to sciences, engineering & beyond— Vision: Have domain scientists work w/ Computer Scientists on code

http://moss.csc.ncsu.edu/~mueller/cluster/arc/

Equipment donations welcome Ideas how to improve ARC? let us know

— Qs? send to mailing list (once you have an account)— request an account: email dfiala<at>ncsu.edu

–Research topic, abstract, and compute requirements/time– Must include your unity ID– NCSU Students: Advisor sends email as means of their approval– Non-NCSU: same + preferred username + hostname(your remote login location.

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Slides provided by David Fiala

Edited by Frank Mueller

Current as of May 11, 2011.